Admission requirements
The courses:
Introduction to Network Science
Essentials of Mathematics, Data Science and Programming
Description
Networks are effective representations to study a wide range of systems composed of interconnected/interacting components, such as social, biological, financial, and transportations systems. In this course, students will gain hands-on experience in developing a project on network structured datasets, building on the knowledge gained in other courses of the Network Science minor. In this project, they will work on solving a real-world problem, such as identifying communities in a network, identify key players in a network, model the evolution of a network, how to assess the robustness of a network, finding suspicious transactions in banking domain, finding fake account on social media, design chemical reactions using reaction network, etc. using network science technique/methodology. The first part of the project will consist of implementing a method described in the literature to real-world data. In the second part of the project, they will compare their method with other baselines.
Course outline
- Beside the first introductory lesson, the rest of the course will be organized in the form of lab sessions where the students will work on their project.
- Group project.
Course Objectives
A student who has successfully completed the course is able to:
Apply a network science method to real-world network data, critically evaluate its outcomes, and interpret key findings.
Present and discuss a scientific paper on network science, effectively communicating insights through presentations.
Collaboratively work to analyze, compare, and synthesize your solution with other baselines.
Co-author a research report and present the developed project
Create and deliver a project on network science using the network science techniques with team.
Timetable
In MyTimetable, you can find all course and programme schedules, allowing you to create your personal timetable. Activities for which you have enrolled via MyStudyMap will automatically appear in your timetable.
Mode of Instruction
lectures and lab sessions
Assessment method
50% Mid-term project evaluation – Presentation/Project Report
50% Final group project evaluation - Presentation and Project Report
Attendance in lab sessions is strongly advised, but not compulsory. Each lab session will be dedicated to providing feedback and help students in developing their project.
Reading list
tbd
Registration
tbd
Contact
Akrati Saxena (a.saxena@liacs.leidenuniv.nl). Office hours tbd.
Alberto Ceria (a.ceria@liacs.leidenuniv.nl). Office hours tbd.
Remarks
part of the minor Network Science for a Connected World